OpenCV 无缝融合seamlessClone()，调试颜色colorChange()，消除高亮illuminationChange()，纹理扁平化textureFlattening()（OpenCV案例源码cloning_demo.cpp解读）

【知识点1】

把一幅图无缝融合到另一幅图里，主要是seamlessClone() 的使用。

seamlessClone( InputArray src, InputArray dst, InputArray mask, Point p, OutputArray blend, int flags);

注意需要三幅图合为一幅图，src与mask抠图（逻辑与，尺寸一致），把抠出的图融合到dst中的p位置处（抠出的图尺寸≤dst图）。p位置也是抠出的图的中心。

3种融合模式flags：NORMAL_CLONE = 1，MIXED_CLONE  = 2，MONOCHROME_TRANSFER = 3

#include<opencv2\opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main()
{
    string folder = "cloning/Normal_Cloning/"; //可更换Mixed_Cloning,Monochrome_Transfer目录
    string original_path1 = samples::findFile(folder + "source1.png");
    string original_path2 = samples::findFile(folder + "destination1.png");
    string original_path3 = samples::findFile(folder + "mask.png");

    Mat source = imread(original_path1, IMREAD_COLOR);
    Mat destination = imread(original_path2, IMREAD_COLOR);
    Mat mask = imread(original_path3, IMREAD_COLOR);

    Mat result;
    Point p;
    p.x = destination.size().width / 2;
    p.y = destination.size().height / 2;

    seamlessClone(source, destination, mask, p, result, NORMAL_CLONE); //可更换MIXED_CLONE，MONOCHROME_TRANSFER

    imshow("Output", result);
    imwrite("cloned.png", result);

    waitKey(0);
    return 0;
}

【知识点2】

对感兴趣区域进行颜色调整。如下图，花朵更鲜艳。主要是colorChange()函数的使用。

#include<opencv2\opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main()
{
    string folder = "cloning/color_change/";
    string original_path1 = samples::findFile(folder + "source1.png");
    string original_path2 = samples::findFile(folder + "mask.png");

    Mat source = imread(original_path1, IMREAD_COLOR);
    Mat mask = imread(original_path2, IMREAD_COLOR);

    Mat result;
    colorChange(source, mask, result, 1.5, .5, .5); //mask定位source中的roi区域，调整该区域颜色r，g，b

    imshow("Output", result);
    imwrite("cloned.png", result);

    waitKey(0);
    return 0;
}

【知识点3】

消除高亮区域，illuminationChange()函数的使用。alpha，beta两个参数共同决定消除高光后图像的模糊程度（范围0~2，0比较清晰，2比较模糊）

#include<opencv2\opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main()
{
    string folder = "cloning/Illumination_Change/";
    string original_path1 = samples::findFile(folder + "source1.png");
    string original_path2 = samples::findFile(folder + "mask.png");

    Mat source = imread(original_path1, IMREAD_COLOR);
    Mat mask = imread(original_path2, IMREAD_COLOR);

    Mat result;

    illuminationChange(source, mask, result, 0.2f, 0.4f); //消除source中mask锁定的高亮区域，后两个参数0-2调整

    imshow("Output", result);
    imwrite("cloned.png", result);

    waitKey(0);
    return 0;
}

【知识点4】

纹理扁平化，边缘检测器选取的边缘越少（选择性越强），边缘映射就越稀疏，扁平化效果就越明显。textureFlattening()函数的使用。

#include<opencv2\opencv.hpp>
#include<iostream>

using namespace cv;
using namespace std;

int main()
{
    string folder = "cloning/Texture_Flattening/";
    string original_path1 = samples::findFile(folder + "source1.png");
    string original_path2 = samples::findFile(folder + "mask.png");

    Mat source = imread(original_path1, IMREAD_COLOR);
    Mat mask = imread(original_path2, IMREAD_COLOR);

    Mat result;

    textureFlattening(source, mask, result, 30, 45, 3); //对mask锁定的source中的区域进行纹理扁平化，低阈值，高阈值，核尺寸

    imshow("Output", result);
    imwrite("cloned.png", result);

    waitKey(0);
    return 0;
}